This handy technical reference provides extensive coverage of Wiener and Kalman filtering along with a development of least squares estimation, maximum likelihood estimation, and maximum a posteriori estimation based on discrete-time measurements. There is strong emphasis on how they interrelate and fit together to form a systematic development of optimal estimation. Examples and exercises refer to MATLAB software.
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This handy technical reference provides extensive coverage of Wiener and Kalman filtering along with a development of least squares estimation, maximum likelihood estimation, and maximum a posteriori estimation based on discrete-time measurements. There is strong emphasis on how they interrelate and fit together to form a systematic development of optimal estimation. Examples and exercises refer to MATLAB software.
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